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Acoustic generator for evoked potentials stimulation
Škutková, Helena ; Rampl, Ivan (referee) ; Chmelař, Milan (advisor)
Evoked potentials are electric brain response to external stimulus. They are important diagnostic no visual method in neurology. For their excitation use of different of kinds stimulation, most often: visual, auditory, somatosenzory, olfactory and gustatory. Evoked potentials are objective method for measurement sense perception. This master’s thesis is specialized to auditory evoked potentials and design acoustic generator for their stimulation. Auditory evoked potentials are primary used for objective audiometry, but they have another usage. In the first place, application is specialized on health sector. The aim of this master’s thesis is compact specified medical requirements with available technical resources.
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Human Sleep EEG Analysis
Sadovský, Petr ; Rozman, Jiří (advisor)
This thesis deals with analysis and processing of the Sleep Electroencephalogram (EEG) signals. The scope of this thesis can be split into several areas. The first area is application of the Independent Component Analysis (ICA) method for EEG signal analysis. A model of EEG signal formation is proposed and conditions under which this model is valid are examined. It is shown that ICA can be used to remove non-deterministic artifacts contained in the EEG signals. The second area of interest is analysis of stationarity of the Sleep EEG signal. Methods to identify stationary signal segments and to analyze statistical properties of these stationary segments are presented. The third area of interest focuses on spectral analysis of the Sleep EEG signals. Analyses are performed that shows the processes that form particular parts of EEG signals spectrum. Also, random signals that are an integral part of the EEG signals analysis are performed. The last area of interest focuses on elimination of the transition processes that are caused by the filtering of the short EEG signal segments.
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Controlling a Virtual Robot Using a Hybrid Brain-Computer Interface with Visual and Auditory Cues
Prášil, Matěj ; Hrubý, Martin (referee) ; Tinka, Jan (advisor)
This work deals with the control of a virtual robot using a hybrid interface between the brain and a computer in response to visual and auditory evoked potentials, EEG signal analysis and processing. OpenBCI hardware is used for scanning. I studied the methods needed for signal processing and designed applications. The output is two applications, one for controlling a virtual robot and the other for signal processing and classification. The average accuracy of signal classification on real data is low, only 22.35%
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Automated Detection of graphic elements in EEG signal
Jančová, Ivana ; Ronzhina, Marina (referee) ; Bubník, Karel (advisor)
This thesis deals with the analysis of EEG, namely detection of graphic elements. The aim of the thesis is to describe methods suitable for detection of graphic elements and implementation of the two methods in MATLAB. The first part of the thesis describes the basics rhythms, artifacts and epileptiform transients occurring in the EEG. The second part deals with the methods of detection and their mutual comparison. The discussed methods are spectral analysis, correlation analysis, wavelet transform, cluster analysis and matched filter. Other parts of the thesis describe the database PhysioBank and implementation of the correlation analysis and matched filter. In the last part is the comparison of the success of selected methods and comparison is done by calculating sensitivity and positive predictive value.
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Dectection of brain wakefulness from scalp EEG data with higher order statistics
Semeráková, Nikola ; Ronzhina, Marina (referee) ; Labounek, René (advisor)
Presented master's thesis deals with detection of brain wakefulness from scalp EEG data with higher order statistics. Part of the thesis is a description of electroencephalography, from the method of signal generation, sensing, electroencephraphy, EEG signal artifacts, frequency bands of EEG signal to its possible processing. Furthermore, the concept of mental fatigue and the possibility of its detection in the EEG signal is described. Subsequently, the principles of higher statistical methods of PCA and ICA and the specific possibilities of decomposition of EEG signal are described using these methods, from which the method of group spatial-frequency ICA was chosen as a suitable method for selection of partial oscillatory sources in EEG signal. In the next part there is described a method of acquisition of data, a the suggestion of solution with selected method and a description of the implemented algorithm, that was applied to real 256-lead scalp EEG data captured during a block task focused on subject allertnes. The absolute and relative power of the EEG signal was decomposed. From the achieved results, we observe that the fluctuations of the spatial frequency patterns of relative power (especially for theta and alpha bands) significantly more closely correspond with the change of reaction time and the error of the subjects performing the task. These observations appear to be relatively consistent with previously published literature, and the current study shows that spatial frequency ICA is able to blindly isolate space-frequency patterns whose fluctuations are statistically significantly correlated with parameters (reaction time, error rate) directly flowing from the given task.
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Evoked potentials and its sensing
Fabianová, Katarína ; Janoušek, Oto (referee) ; Chmelař, Milan (advisor)
An electrical activity of the brain can be spontaneous (a signal is produced during the life of the individual) or can be evoked (a reply to the external above threshold stimulus). This work is largely dedicated to evoked potentials by which the brain reacts normal or abnormal to given external stimuli (sound, light, etc.). The main essence of this work is a project of the simple acoustical generator for the research of evoked potentials. This acoustical generator is also useable in connection with the EEG device from Alien Technic without any intervention to this device. Acoustical evoked potentials belong to the most widely used objective examinations of the sense of hearing.
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Brain Signals Visualization
Ševčík, Ivan ; Drahanský, Martin (referee) ; Košík, Michal (advisor)
EEG je neinvazivní metoda pro měření mozkové aktivity, která poskytuje důležitý náhled do činnosti lidského mozku. Tato práce prezentuje aplikaci, která slouží jako vizuálni nástroj pro analýzu EEG dat. Koncept aplikace je založen na jiných existujících řešeních, které byly v rámci práce analyzovány. Aplikace kombinuje prohlížeč signálů ve formě vícenásobného čárového grafu s 2D a 3D vizualizacemi užitečnými pro rozpoznání specifické mozkové aktivity. Součásti aplikace je i sada metod pro zpracování signálu. Závěr práce je věnován shrnutí dosažených výsledků a plánů pro další vývoj aplikace.
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Processing of EEG signals in frequency domain
Nováková, Jarmila ; Potočňák, Tomáš (referee) ; Kozumplík, Jiří (advisor)
Sleep EEG is occupied by this project. It is aimed at processing signal which precede test of stationarity. It also deals with the issue of stationarity of sleep EEG with indicating of three types of segmentations. Principles of three types of segmentation are explained and their realization is compiled in the environment of Matlab by the way which enables to choose different input parameters. The change of stationarity is examined in various stages of sleep with the help of the results thus created functions. Another aspect of this study is the investigation of changes in the development of absolute and relative power over time according to transition between stage of wakefulness and stage of sleep. It is searched for the occurrence of these changes also in the development of the coherence spectra.
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EEG Biofeedback Human Brain - Computer Interface
Kněžík, Jan ; Kořenek, Jan (referee) ; Marušinec, Jaromír (advisor)
This master thesis dwells on EEGbiofeedback (also called Neurofeedback) interface of human brain and the computer and its concrete realization in Java programming language. This system is founded on the basis of the computer, which is accomplishing biological feedback (biofeedback) and the electroencephalography (EEG) by helping that state's scanning of user's brain is realized. By this way is possible to practise the human brain effectively to achieve better concentration, the elimination of sleeping and learning deficiency. Hereafter is the suggestion of direction control of computer mouse by EEG device incorporated, which makes it possible for the man to regulate the direction of the cursor's movement on the screen by the frequency of brain's oscillation. The motivation for solution of this problem is the effort to help to handicapped people to communicate with surrounding world. The introduction of this paper contains the basic facts about human brain, electroencephalography and EEG biofeedback. The following chapters dwell on the specification of claims to developed application, its suggestion and description of actual realization. The final part relates to the BCI (Brain-Computer Interface) systems and suggestion of computer's control by EEGappliance with evaluation of attained results.
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Toolbox for automatic EEG data quality assessment
Meloun, Jan ; Gajdoš, Martin (referee) ; Lamoš, Martin (advisor)
This thesis deals with designing a tool for automatically evaluating the quality of electroencephalographic data. In the theoretical part of the thesis, there is a theoretical basis in the anatomy of the central nervous system and the brain, followed by a description of the origin and propagation of the action potential through the nervous system. Furthermore, the theoretical part of the work is devoted to electroencephalography (EEG) and the description of the EEG recording, including typical artefacts in it. The following describes the methods used to detect and remove artefacts. These are primary methods for extracting data quality features. The practical part of the thesis contains a description of the design of a tool for automatic EEG quality assessment and its testing on artificial and real data. The last part of the work is devoted to the discussion of the results of the success of the detection of channels or sections with artefacts and the possible further extension of the tool.
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